Submitted by:
ID1: 320983216 Name1: Maxim Kolchinsky
ID2: 321340580 Name2: Anna Romanov
The data for this lesson comes from:
> Saigi et al. “MET-Oncogenic and JAK2-Inactivating Alterations Are Independent Factors That Affect Regulation of PD-L1 Expression in Lung Cancer” PLoS ONE. 2018 Jun 13;9(6):e99625. PMID: 24926665.
Purpose: The blockade of immune checkpoints such as PDL1 and PD-1 is being exploited therapeutically in several types of malignancies. Here, we aimed to understand the contribution of the genetics of lung cancer to the ability of tumor cells to escape immunosurveillance checkpoints. Experimental Design: More than 150 primary non-small cell lung cancers, including pulmonary sarcomatoid carcinomas, were tested for levels of the HLA-I complex, PD-L1, tumor-infiltrating CD8þ lymphocytes, and alterations in main lung cancer genes. Correlations were validated in cancer cell lines using appropriate treatments to activate or inhibit selected pathways. We also performed RNA sequencing to assess changes in gene expression after these treatments. Results: MET-oncogenic activation tended to associate with positive PD-L1 immunostaining, whereas STK11 mutations were correlated with negative immunostaining. In MET-altered cancer cells, MET triggered a transcriptional increase of PD-L1 that was independent of the IFNgmediated JAK/STAT pathway. The activation of MET also upregulated other immunosuppressive genes (PDCD1LG2 and SOCS1) and transcripts involved in angiogenesis (VEGFA and NRP1) and in cell proliferation. We also report recurrent inactivating mutations in JAK2 that co-occur with alterations in MET and STK11, which prevented the induction of immunoresponse-related genes following treatment with IFNg. Conclusions: We show that MET activation promotes the expression of several negative checkpoint regulators of the immunoresponse, including PD-L1. In addition, we report inactivation of JAK2 in lung cancer cells that prevented the response to IFNg. These alterations are likely to facilitate tumor growth by enabling immune tolerance and may affect the response to immune checkpoint inhibitors
This data was downloaded from GEO (GSE:GSE109720)
library(readr)
library(dplyr)
library(ggplot2)
rawcounts <- read_csv("data/lung_counts.csv")
metadata <- read_csv("data/lung_metadata.csv")
rawcounts
metadata
library(tibble)
library(tidyr)
# a plotting function
plot_heatmap <- function(km) {
centers <- km$centers %>%
tbl_df() %>%
rownames_to_column('Cluster') %>%
gather(Sample, value, -Cluster) %>%
mutate(
Cluster = factor(Cluster),
Sample = factor(Sample)
)
ggplot(centers,aes(Sample,Cluster)) + geom_tile(aes(fill=value)) + geom_text(aes(label = round(value, 1)), angle=90, size=4) + theme(axis.text.x=element_text(angle=90, vjust=0.5, hjust=0, size=12))
}
# cluster the genes
rawcounts_RN<- data.frame(rawcounts, row.names=1)
km <- kmeans(rawcounts_RN,5)
km$centers
## AE1148 AE1149 AE1150 AE1151 AE1152 AE1153
## 1 204.3794 260.8659 184.8346 225.175 226.5053 263.4797
## 2 31052.4260 42212.6686 27571.1893 34696.260 32887.3373 41325.6095
## 3 261075.5000 355397.5000 249188.5000 298081.500 312029.0000 330232.5000
## 4 101059.4762 147734.7143 89713.5238 117618.429 120754.0000 151602.5238
## 5 6589.0833 8841.2332 6127.4839 7358.684 7346.2171 8890.0477
## AE1154 AE1155 AE1156 AE1157 AE1158 AE1159
## 1 177.6818 222.9686 196.5011 232.7849 189.8281 212.521
## 2 26505.6568 33457.2663 29596.4379 37330.6331 30042.5799 32418.935
## 3 222399.5000 302143.5000 258949.5000 295158.0000 257717.0000 284918.500
## 4 90998.6190 124462.2857 104368.4286 134149.9048 106395.0952 117189.476
## 5 5868.3233 7272.5940 6356.2941 8001.1913 6352.8116 7040.299
## AE1160 AE1161 AE1162 AE1163 AE1164 AE1165
## 1 242.584 180.0566 253.0504 219.7236 191.4948 214.1561
## 2 35868.917 27201.2367 34315.4142 31814.4260 29037.9941 29120.4734
## 3 413308.500 281465.5000 419312.0000 335008.5000 264320.5000 344465.0000
## 4 143324.762 104374.0952 132841.0000 122184.8571 107568.4286 112637.7143
## 5 7666.075 5913.3574 7290.1723 6847.2006 6203.9289 6185.2936
## AE1166 AE1167 AE1168 AE1169 AE1170 AE1171
## 1 241.4646 198.3505 238.9257 253.7209 189.6234 218.4082
## 2 34757.7219 29575.0533 32625.8402 36791.6982 27468.7456 31881.7219
## 3 384117.5000 304171.0000 421639.5000 605629.0000 430845.0000 507135.5000
## 4 135000.0476 111633.0476 126291.2857 169666.4762 124785.2381 141406.8095
## 5 7557.6928 6488.0501 6934.8676 7469.2434 5595.4722 6493.8734
## AE1172 AE1173 AE1174 AE1175 AE1176 AE1177
## 1 185.7504 226.5967 210.5955 222.858 183.9239 211.8739
## 2 27203.1006 33370.0118 31380.9112 29166.260 24118.6923 28170.8698
## 3 422003.5000 530275.0000 492796.5000 382136.500 308577.5000 364062.5000
## 4 117254.7619 146959.6667 137927.1429 127871.333 104154.3333 123308.0952
## 5 5550.7936 6760.0141 6311.3476 6946.255 5771.8062 6654.9367
## AE1178 AE1179 AE1180
## 1 165.6252 178.0214 225.1644
## 2 21687.6036 23821.4024 29880.8935
## 3 280669.0000 308508.0000 400801.0000
## 4 94938.3333 104582.6190 133835.4286
## 5 5181.0136 5586.3374 7055.9640
table(km$cluster)
##
## 1 2 3 4 5
## 56101 169 2 21 2054
plot_heatmap(km)
# apply log scaling
rawcounts_RN
rawcounts_log = log10(1+rawcounts_RN)
km <- kmeans(rawcounts_log,5)
km$centers
## AE1148 AE1149 AE1150 AE1151 AE1152 AE1153
## 1 1.83702486 1.90449010 1.80528135 1.87937096 1.91101067 1.93563878
## 2 2.81040539 2.89376012 2.74982450 2.84936858 2.84983522 2.88789617
## 3 0.71791421 0.78602626 0.72984850 0.76302505 0.80766282 0.82175669
## 4 3.53276033 3.64441691 3.48151022 3.57701118 3.57459879 3.63265423
## 5 0.03383464 0.04070399 0.03671669 0.03778014 0.04129412 0.04544332
## AE1154 AE1155 AE1156 AE1157 AE1158 AE1159
## 1 1.78006310 1.89533169 1.87809325 1.88631317 1.83941134 1.88495685
## 2 2.70968337 2.83817649 2.79121332 2.84003298 2.75247788 2.81786796
## 3 0.71051633 0.78979111 0.78077052 0.78193158 0.75910351 0.77910880
## 4 3.44101008 3.56260329 3.51018120 3.59660666 3.47847058 3.55258537
## 5 0.03525637 0.04041237 0.03816456 0.03878697 0.03846926 0.04042839
## AE1160 AE1161 AE1162 AE1163 AE1164 AE1165
## 1 1.72482441 1.57883609 1.78440280 1.69279157 1.60659796 1.7010291
## 2 2.85287266 2.70356689 2.87962990 2.81338935 2.73439810 2.8057634
## 3 0.77984051 0.67734644 0.83405850 0.75250277 0.68961210 0.7527325
## 4 3.60604751 3.47295929 3.59456780 3.55882952 3.49697270 3.5233552
## 5 0.04228286 0.03482157 0.04934553 0.04090791 0.03483581 0.0403937
## AE1166 AE1167 AE1168 AE1169 AE1170 AE1171
## 1 1.72148517 1.61817379 1.7524813 1.86774760 1.73868498 1.80511054
## 2 2.84957931 2.74917160 2.8518106 2.86213862 2.73553353 2.79738975
## 3 0.76919789 0.68795606 0.7883144 0.97743341 0.86818522 0.92806724
## 4 3.60198434 3.51694702 3.5721743 3.58005983 3.45251003 3.51893319
## 5 0.04050045 0.03600679 0.0450553 0.07469409 0.05966218 0.06738637
## AE1172 AE1173 AE1174 AE1175 AE1176 AE1177
## 1 1.72950970 1.81404225 1.78408763 1.66421354 1.57459353 1.63890307
## 2 2.72540850 2.81188997 2.78091975 2.77071334 2.68425641 2.74768434
## 3 0.85480390 0.93153736 0.91315560 0.72290179 0.65421636 0.71199777
## 4 3.44953976 3.53572936 3.50371977 3.54632120 3.46398147 3.52648075
## 5 0.05931824 0.06742127 0.06470466 0.04220111 0.03480657 0.04185064
## AE1178 AE1179 AE1180
## 1 1.53851602 1.56294388 1.66357207
## 2 2.64155117 2.67351055 2.77413859
## 3 0.63276763 0.63743320 0.72606404
## 4 3.41852004 3.45101801 3.55283952
## 5 0.03489193 0.03510521 0.04234835
table(km$cluster)
##
## 1 2 3 4 5
## 3986 5706 6081 4922 37652
plot_heatmap(km)
# load DE gene list
DE_res <- read_csv("data/sigresults.csv")
DE_genes <- DE_res$row
nrow(DE_genes)
## NULL
# filter differentially expressed genes
dat_filtered = rawcounts_log[DE_genes,]
# utils::View(dat_filtered) #show all rows (sanity test)
dat_filtered
km <- kmeans(dat_filtered,5)
km$centers
## AE1148 AE1149 AE1150 AE1151 AE1152 AE1153 AE1154
## 1 3.727994 3.8458092 3.6789046 3.7737672 3.7712481 3.8353965 3.6410604
## 2 1.675386 1.7422638 1.6510038 1.7196991 1.7529987 1.7768871 1.6264149
## 3 0.765454 0.8311759 0.7725323 0.8022541 0.8501813 0.8652445 0.7607886
## 4 2.462767 2.5365933 2.4048882 2.5013205 2.5130691 2.5449090 2.3716124
## 5 3.092749 3.1880818 3.0341405 3.1334550 3.1313785 3.1766484 2.9912540
## AE1155 AE1156 AE1157 AE1158 AE1159 AE1160 AE1161
## 1 3.7607523 3.7065729 3.8005181 3.6777912 3.7524569 3.806034 3.6761759
## 2 1.7360776 1.7220732 1.7293267 1.6861379 1.7252916 1.555795 1.4185047
## 3 0.8368235 0.8265967 0.8244078 0.8075869 0.8277963 0.794030 0.6944175
## 4 2.5022342 2.4616528 2.4920190 2.4193247 2.4803901 2.458831 2.2998114
## 5 3.1179479 3.0678641 3.1348971 3.0303171 3.1023517 3.157674 3.0154272
## AE1162 AE1163 AE1164 AE1165 AE1166 AE1167 AE1168
## 1 3.7855799 3.7573965 3.6983879 3.7145398 3.8002028 3.718978 3.7639160
## 2 1.6178264 1.5275811 1.4457768 1.5358955 1.5550413 1.454924 1.5847437
## 3 0.8437592 0.7699717 0.7109858 0.7699636 0.7789845 0.707016 0.8029044
## 4 2.5035578 2.4215862 2.3286569 2.4247827 2.4515474 2.342389 2.4701160
## 5 3.1672278 3.1142560 3.0444352 3.0951235 3.1562218 3.061380 3.1431866
## AE1169 AE1170 AE1171 AE1172 AE1173 AE1174 AE1175
## 1 3.767829 3.639808 3.708035 3.639053 3.725154 3.693315 3.7348540
## 2 1.687502 1.557819 1.624723 1.550872 1.634168 1.606828 1.4788446
## 3 1.161839 1.047954 1.115588 1.034681 1.117392 1.097845 0.7847045
## 4 2.501827 2.375108 2.439605 2.363916 2.449952 2.419957 2.3747731
## 5 3.161516 3.034307 3.096639 3.026127 3.112850 3.080786 3.0987064
## AE1176 AE1177 AE1178 AE1179 AE1180
## 1 3.6533539 3.7155625 3.6073938 3.6401817 3.7419750
## 2 1.3898792 1.4576452 1.3570359 1.3815305 1.4811532
## 3 0.7185449 0.7670533 0.6898521 0.6939588 0.7796293
## 4 2.2852559 2.3481420 2.2440608 2.2728393 2.3748266
## 5 3.0145756 3.0772103 2.9698454 3.0019990 3.1036586
table(km$cluster)
##
## 1 2 3 4 5
## 2659 3066 3832 3205 5195
plot_heatmap(km)
# a plotting function
plot_heatmap <- function(km) {
centers <- km$centers %>%
tbl_df() %>%
rownames_to_column('Cluster') %>%
gather(Gene, value, -Cluster) %>%
mutate(
Cluster = factor(Cluster),
Gene = factor(Gene)
)
ggplot(centers,aes(Cluster,Gene)) + geom_tile(aes(fill=value)) + theme(axis.text.x=element_text(angle=0, vjust=0.5, hjust=0, size=12)) + theme(axis.text.y=element_blank())
}
#filter example
rawcounts_filtered <- rawcounts_RN %>% sample_n(500)
# cluster the samples
km <- kmeans(t(rawcounts_filtered),3)
# t function turns samples into rows and genes into columns, this way genes are the features and samples are clustered
km$centers
## ENSG00000105137.12 ENSG00000188729.6 ENSG00000173705.8 ENSG00000253339.1
## 1 529.90909 0.09090909 195.4545 0.00
## 2 74.16667 0.91666667 645.5833 1.75
## 3 128.20000 0.20000000 14.4000 0.00
## ENSG00000134259.3 ENSG00000258420.1 ENSG00000231706.2 ENSG00000281394.1
## 1 180.7273 0 0 0
## 2 5.7500 0 0 0
## 3 10.9000 0 0 0
## ENSG00000204231.10 ENSG00000263603.1 ENSG00000242259.8 ENSG00000247095.2
## 1 1204.545 1.181818 342.9091 139.81818
## 2 1114.833 2.416667 718.1667 57.83333
## 3 2220.500 5.200000 435.9000 61.90000
## ENSG00000235862.2 ENSG00000166313.18 ENSG00000071242.11
## 1 0 41.00 1000.636
## 2 0 25.75 864.500
## 3 0 152.20 1134.100
## ENSG00000243854.3 ENSG00000103363.14 ENSG00000252035.1 ENSG00000281566.2
## 1 0.3636364 4620.545 0 0.00000
## 2 0.4166667 3500.000 0 15.33333
## 3 1.0000000 3326.600 0 0.00000
## ENSG00000233121.1 ENSG00000189348.6 ENSG00000241622.1 ENSG00000156273.15
## 1 0.18181818 0 0.00000000 2523.7273
## 2 0.08333333 0 0.08333333 975.3333
## 3 0.00000000 0 0.10000000 1419.1000
## ENSG00000227630.3 ENSG00000267275.1 ENSG00000121380.12 ENSG00000228651.1
## 1 11.00000 0.0 26.18182 0.00000000
## 2 10.33333 0.0 1.50000 0.08333333
## 3 10.00000 0.2 89.30000 0.00000000
## ENSG00000233117.2 ENSG00000278771.1 ENSG00000104970.10 ENSG00000234110.1
## 1 8.6363636 1.363636 0.00000000 0
## 2 0.1666667 11.416667 0.08333333 0
## 3 144.7000000 7.000000 0.00000000 0
## ENSG00000182218.9 ENSG00000233693.1 ENSG00000115461.4 ENSG00000164713.9
## 1 25.00000 0.6363636 6192.091 932.7273
## 2 33.58333 0.9166667 5020.500 4405.7500
## 3 1.40000 0.1000000 318.300 1477.6000
## ENSG00000249433.1 ENSG00000240354.1 ENSG00000204622.11 ENSG00000244932.2
## 1 0 0 10.09091 0
## 2 0 0 5.00000 0
## 3 0 0 22.30000 0
## ENSG00000239820.3 ENSG00000255149.1 ENSG00000137809.16
## 1 0.18181818 0 121.090909
## 2 0.08333333 0 5.666667
## 3 0.50000000 0 344.200000
## ENSG00000100427.15 ENSG00000160213.6 ENSG00000221858.3 ENSG00000264176.1
## 1 0.2727273 5661.545 0 0.27272727
## 2 5.6666667 4871.083 0 0.08333333
## 3 0.3000000 2072.300 0 0.80000000
## ENSG00000197444.9 ENSG00000258944.1 ENSG00000277630.4 ENSG00000237823.1
## 1 20.63636 5.727273 0 0
## 2 18.41667 5.250000 0 0
## 3 8.60000 4.500000 0 0
## ENSG00000254019.1 ENSG00000073331.17 ENSG00000115474.6 ENSG00000122728.6
## 1 0.0000000 510.6364 0.0 2.00
## 2 0.1666667 486.2500 0.0 4.75
## 3 0.0000000 1281.7000 9.3 2.00
## ENSG00000204456.4 ENSG00000196578.4 ENSG00000167751.12 ENSG00000277418.1
## 1 0 0.00000000 0.09090909 0
## 2 0 0.08333333 1.16666667 0
## 3 0 0.00000000 1.90000000 0
## ENSG00000204628.11 ENSG00000169900.7 ENSG00000233214.1 ENSG00000213977.7
## 1 38426.36 0.00000000 0.09090909 10491.36
## 2 29081.25 0.08333333 0.00000000 2322.00
## 3 28427.90 0.00000000 0.00000000 5111.30
## ENSG00000230709.1 ENSG00000198756.10 ENSG00000197915.5 ENSG00000235045.2
## 1 0.09090909 52.00000 0.5454545 0.27272727
## 2 0.08333333 10.33333 0.4166667 0.08333333
## 3 0.00000000 17.00000 0.1000000 0.00000000
## ENSG00000254630.1 ENSG00000264128.2 ENSG00000238007.1 ENSG00000162722.8
## 1 0.00000000 0 0 0.0
## 2 0.08333333 0 0 149.5
## 3 0.20000000 0 0 0.1
## ENSG00000224374.1 ENSG00000254528.7 ENSG00000105173.13 ENSG00000171747.8
## 1 0 0.00000 958.6364 2.636364
## 2 0 43.58333 1644.4167 6.750000
## 3 0 0.20000 305.6000 2.700000
## ENSG00000225171.2 ENSG00000173452.13 ENSG00000198887.8 ENSG00000226670.1
## 1 1.909091 0.00000000 2455.727 0
## 2 2.166667 0.08333333 2219.500 0
## 3 1.100000 0.00000000 4153.500 0
## ENSG00000175414.6 ENSG00000267409.1 ENSG00000236242.1 ENSG00000225449.3
## 1 9.727273 0 6.818182 0.00000
## 2 114.333333 0 3.416667 15.91667
## 3 1.900000 0 0.300000 0.00000
## ENSG00000270669.1 ENSG00000077942.18 ENSG00000256136.1
## 1 0 3679.636 0
## 2 0 2487.667 0
## 3 0 322.200 0
## ENSG00000175063.16 ENSG00000210174.1 ENSG00000263321.1 ENSG00000243011.3
## 1 5150.727 0 0 0
## 2 2794.750 0 0 0
## 3 3831.600 0 0 0
## ENSG00000219553.2 ENSG00000170967.4 ENSG00000223546.6 ENSG00000131142.13
## 1 0.3636364 0.0000000 140.18182 0.09090909
## 2 0.9166667 0.1666667 96.33333 0.08333333
## 3 0.2000000 0.0000000 172.90000 0.20000000
## ENSG00000226950.6 ENSG00000141040.14 ENSG00000270837.1 ENSG00000235661.3
## 1 820.0909 0.00000 0 0
## 2 2041.1667 90.08333 0 0
## 3 1919.6000 38.70000 0 0
## ENSG00000212316.1 ENSG00000277196.4 ENSG00000225603.3 ENSG00000253833.1
## 1 0 145.6364 0.3636364 0.09090909
## 2 0 327.1667 0.1666667 0.91666667
## 3 0 18.1000 0.4000000 1.00000000
## ENSG00000156471.12 ENSG00000227050.1 ENSG00000269320.1 ENSG00000279874.1
## 1 4656.909 0.00 0 0
## 2 4463.417 0.25 0 0
## 3 6881.000 0.40 0 0
## ENSG00000228496.1 ENSG00000275107.1 ENSG00000232406.6 ENSG00000179899.8
## 1 0.0 0 0.09090909 31.45455
## 2 0.5 0 0.66666667 89.83333
## 3 0.0 0 3.50000000 168.20000
## ENSG00000219074.1 ENSG00000164220.6 ENSG00000267418.1 ENSG00000212335.1
## 1 0 20.27273 0 0
## 2 0 116.50000 0 0
## 3 0 1.00000 0 0
## ENSG00000207750.1 ENSG00000234385.1 ENSG00000250714.3 ENSG00000169696.15
## 1 0 0 5.818182 798.7273
## 2 0 0 2.416667 1146.2500
## 3 0 0 3.200000 869.5000
## ENSG00000220695.1 ENSG00000227088.1 ENSG00000189366.9 ENSG00000211941.3
## 1 0.7272727 0 497.63636 0
## 2 0.4166667 0 47.58333 0
## 3 0.6000000 0 104.40000 0
## ENSG00000229722.1 ENSG00000261703.1 ENSG00000123144.10 ENSG00000280081.3
## 1 0 0 2842.636 0.000000
## 2 0 0 1794.000 2.666667
## 3 0 0 2128.100 0.000000
## ENSG00000271616.1 ENSG00000207515.1 ENSG00000240625.3 ENSG00000128602.9
## 1 0.0000000 0 0.00 82.90909
## 2 0.1666667 0 0.25 436.00000
## 3 0.1000000 0 0.60 8.80000
## ENSG00000088247.17 ENSG00000183486.12 ENSG00000147885.4
## 1 6882.909 3099.636 0
## 2 6795.167 10.250 0
## 3 9260.200 707.600 0
## ENSG00000266265.2 ENSG00000257504.1 ENSG00000161920.9 ENSG00000284116.1
## 1 1.363636 0.00 507.6364 98.54545
## 2 8.000000 0.25 394.0000 23.83333
## 3 0.100000 0.00 381.4000 126.40000
## ENSG00000233489.1 ENSG00000164934.13 ENSG00000252716.1 ENSG00000249041.1
## 1 0 3858.818 0 0
## 2 0 5296.500 0 0
## 3 0 3655.100 0 0
## ENSG00000250424.4 ENSG00000283154.2 ENSG00000272827.1 ENSG00000271475.1
## 1 0.2727273 899.3636 0 0.00000000
## 2 0.9166667 401.2500 0 0.08333333
## 3 0.1000000 768.5000 0 0.10000000
## ENSG00000268555.1 ENSG00000235028.3 ENSG00000154265.15 ENSG00000187870.7
## 1 0.18181818 0.5454545 580.7273 0.000000
## 2 0.08333333 0.4166667 1245.1667 5.083333
## 3 0.00000000 0.0000000 129.6000 5.000000
## ENSG00000245146.6 ENSG00000254136.1 ENSG00000188039.13 ENSG00000202217.1
## 1 81.18182 0 40.45455 0
## 2 103.16667 0 83.50000 0
## 3 109.00000 0 107.70000 0
## ENSG00000223965.2 ENSG00000232463.1 ENSG00000255234.5 ENSG00000176160.10
## 1 0 0 0.9090909 0.2727273
## 2 0 0 4.0833333 0.2500000
## 3 0 0 1.0000000 0.4000000
## ENSG00000122136.13 ENSG00000262899.1 ENSG00000256994.1
## 1 0.00 0.09090909 0.00000000
## 2 0.25 0.00000000 0.08333333
## 3 0.10 0.00000000 0.00000000
## ENSG00000099715.14 ENSG00000241095.1 ENSG00000211863.1 ENSG00000234812.1
## 1 0 0.8181818 0 0
## 2 0 2.1666667 0 0
## 3 0 1.3000000 0 0
## ENSG00000006611.15 ENSG00000241612.1 ENSG00000133818.13
## 1 0.000000 0.7272727 5603.364
## 2 3.333333 0.4166667 1048.167
## 3 0.000000 0.5000000 2631.000
## ENSG00000276707.1 ENSG00000105583.9 ENSG00000267909.2 ENSG00000189184.11
## 1 0 2066.00 1.090909 261.5454545
## 2 0 1508.25 6.416667 0.1666667
## 3 0 1565.40 0.100000 26.8000000
## ENSG00000170502.12 ENSG00000105254.11 ENSG00000231787.4
## 1 759.2727 1246.455 0.0
## 2 1554.9167 1296.833 0.0
## 3 1378.5000 1586.800 0.7
## ENSG00000241003.1 ENSG00000235797.2 ENSG00000008517.16 ENSG00000266097.1
## 1 0.1818182 0.09090909 902.3636 0
## 2 0.8333333 0.08333333 19.5000 0
## 3 0.6000000 0.00000000 861.9000 0
## ENSG00000229056.2 ENSG00000199815.2 ENSG00000201014.1 ENSG00000234055.1
## 1 5.454545 0 0 0
## 2 39.833333 0 0 0
## 3 0.500000 0 0 0
## ENSG00000239215.1 ENSG00000169306.9 ENSG00000223921.1 ENSG00000239595.3
## 1 0 21.0909091 0.00000000 0
## 2 0 0.3333333 0.08333333 0
## 3 0 304.2000000 0.00000000 0
## ENSG00000103351.12 ENSG00000236325.1 ENSG00000255977.1 ENSG00000225905.1
## 1 769.6364 0 0.00000000 1.2727273
## 2 442.1667 0 0.08333333 0.3333333
## 3 2006.8000 0 0.00000000 0.2000000
## ENSG00000140688.16 ENSG00000261335.1 ENSG00000249863.2 ENSG00000271644.1
## 1 2811.273 7.818182 12.45455 0.1818182
## 2 2981.667 26.583333 57.91667 0.2500000
## 3 2787.800 23.700000 8.30000 0.3000000
## ENSG00000254556.1 ENSG00000164161.9 ENSG00000235082.2 ENSG00000182752.9
## 1 0.00 13.18182 8.272727 149.3636
## 2 0.25 0.75000 4.416667 259.5833
## 3 3.20 1.60000 2.400000 53.4000
## ENSG00000144426.18 ENSG00000230982.1 ENSG00000137959.15
## 1 754.4545 0 3089.727
## 2 982.1667 0 139.000
## 3 557.4000 0 3491.500
## ENSG00000187857.4 ENSG00000159399.9 ENSG00000227023.1 ENSG00000253523.1
## 1 0 5701.182 0 0
## 2 0 1531.583 0 0
## 3 0 1710.100 0 0
## ENSG00000252457.1 ENSG00000275002.1 ENSG00000112812.15 ENSG00000275484.1
## 1 0 0 342.9091 8.272727
## 2 0 0 281.6667 16.833333
## 3 0 0 580.9000 8.800000
## ENSG00000218739.9 ENSG00000176087.14 ENSG00000254669.1 ENSG00000198367.3
## 1 987.0909 3883.818 0 0
## 2 1894.5833 3157.083 0 0
## 3 1704.8000 759.000 0 0
## ENSG00000218472.2 ENSG00000104290.10 ENSG00000224677.1 ENSG00000230852.1
## 1 0.0 138.2727 0 0
## 2 0.0 459.7500 0 0
## 3 0.3 310.4000 0 0
## ENSG00000213731.2 ENSG00000101849.15 ENSG00000261663.1 ENSG00000164778.4
## 1 0 840.8182 3.363636 0.000000
## 2 0 3131.2500 3.333333 8.333333
## 3 0 533.6000 8.900000 0.100000
## ENSG00000164185.5 ENSG00000272685.1 ENSG00000128607.13 ENSG00000277413.1
## 1 2.636364 0 1808.455 0
## 2 18.083333 0 1434.167 0
## 3 8.800000 0 1673.900 0
## ENSG00000229595.1 ENSG00000257964.1 ENSG00000115310.17 ENSG00000176230.5
## 1 0.09090909 0.00000000 11159.82 0
## 2 0.00000000 0.08333333 7028.25 0
## 3 0.20000000 0.60000000 7664.80 0
## ENSG00000283657.1 ENSG00000226338.1 ENSG00000227186.1 ENSG00000164171.10
## 1 0 0 0 13511.45
## 2 0 0 0 11408.67
## 3 0 0 0 22331.70
## ENSG00000202081.1 ENSG00000229533.1 ENSG00000242727.2 ENSG00000201684.1
## 1 0 0 0 0.6363636
## 2 0 0 0 1.0833333
## 3 0 0 0 0.7000000
## ENSG00000261418.1 ENSG00000260565.6 ENSG00000274029.1 ENSG00000219951.4
## 1 0.09090909 814.7273 0.2727273 1.181818
## 2 0.33333333 633.6667 0.0000000 0.500000
## 3 0.70000000 1072.8000 0.3000000 0.900000
## ENSG00000246985.7 ENSG00000044446.11 ENSG00000110077.14
## 1 81.72727 1411.545 0.00000000
## 2 33.16667 1027.417 0.08333333
## 3 43.20000 1140.100 0.20000000
## ENSG00000233852.1 ENSG00000111186.12 ENSG00000271304.1
## 1 0.00 185.09091 0
## 2 0.25 16.41667 0
## 3 0.00 13.10000 0
## ENSG00000139793.18 ENSG00000201752.1 ENSG00000165819.11
## 1 1665.818 0 2447.636
## 2 478.250 0 2739.333
## 3 2550.600 0 986.800
## ENSG00000147381.11 ENSG00000266756.1 ENSG00000176834.13
## 1 0.0 0 820.3636
## 2 12636.5 0 1721.5000
## 3 0.1 0 2341.5000
## ENSG00000225942.1 ENSG00000226646.1 ENSG00000080824.18 ENSG00000258107.1
## 1 0.09090909 0 81909.73 0
## 2 0.00000000 0 91225.67 0
## 3 0.00000000 0 61063.60 0
## ENSG00000255146.1 ENSG00000162976.12 ENSG00000265912.1
## 1 0.09090909 509.9091 0.7272727
## 2 0.83333333 572.7500 0.5833333
## 3 0.00000000 145.2000 1.1000000
## ENSG00000167614.13 ENSG00000201558.1 ENSG00000100867.14
## 1 0.8181818 0.3636364 186.7273
## 2 12.6666667 1.0833333 798.1667
## 3 45.0000000 0.2000000 148.6000
## ENSG00000224089.3 ENSG00000204687.4 ENSG00000258914.1 ENSG00000267774.2
## 1 0 0 0 6.6363636
## 2 0 0 0 0.1666667
## 3 0 0 0 0.5000000
## ENSG00000271595.1 ENSG00000211783.3 ENSG00000263821.1 ENSG00000201839.1
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## ENSG00000249348.1 ENSG00000212939.2 ENSG00000236231.1 ENSG00000149634.4
## 1 31.45455 0.00000000 0 21.18182
## 2 45.41667 0.08333333 0 4.50000
## 3 36.00000 0.10000000 0 24.10000
## ENSG00000197712.11 ENSG00000055211.12 ENSG00000119660.4
## 1 1000.545 1309.818 0.0000000
## 2 1612.250 686.000 0.1666667
## 3 461.600 1284.100 0.0000000
## ENSG00000241127.7 ENSG00000228734.2 ENSG00000185477.4 ENSG00000253820.1
## 1 885.0000 0 0.5454545 0
## 2 273.4167 0 1647.0833333 0
## 3 407.0000 0 0.3000000 0
## ENSG00000257472.1 ENSG00000249915.7 ENSG00000180667.10 ENSG00000283491.1
## 1 0 17560.818 2066.909 0.6363636
## 2 0 7014.417 1528.583 2.3333333
## 3 0 2361.700 602.200 2.6000000
## ENSG00000240583.11 ENSG00000205424.1 ENSG00000124205.15
## 1 110.09091 0 0.0000000
## 2 25.08333 0 0.3333333
## 3 13.10000 0 0.0000000
## ENSG00000248850.1 ENSG00000203780.10 ENSG00000161904.11
## 1 0 15.00 2602.545
## 2 0 169.25 1360.000
## 3 0 324.00 2604.800
## ENSG00000213331.4 ENSG00000227882.1 ENSG00000230716.3 ENSG00000143367.15
## 1 0.8181818 0 10.72727 3694.909
## 2 0.1666667 0 13.75000 3116.000
## 3 0.2000000 0 8.90000 1930.000
## ENSG00000175294.5 ENSG00000104714.13 ENSG00000005513.9 ENSG00000259622.1
## 1 26.000000 441.4545 0.2727273 0
## 2 5.166667 231.7500 7.2500000 0
## 3 75.300000 542.8000 14.5000000 0
## ENSG00000228252.9 ENSG00000254921.1 ENSG00000146039.10 ENSG00000279378.1
## 1 0.18181818 0 0.00000000 0.0000000
## 2 0.08333333 0 0.08333333 0.4166667
## 3 0.50000000 0 0.00000000 0.0000000
## ENSG00000161640.15 ENSG00000202224.1 ENSG00000237260.1 ENSG00000269001.2
## 1 0.00 0 0.1818182 381.54545
## 2 0.25 0 0.5833333 69.41667
## 3 0.00 0 0.1000000 216.40000
## ENSG00000223904.2 ENSG00000166793.10 ENSG00000267096.1 ENSG00000225836.1
## 1 0.0 1.818182 16.636364 0
## 2 0.0 0.250000 8.666667 0
## 3 0.1 25.100000 13.800000 0
## ENSG00000259848.8 ENSG00000242628.5 ENSG00000223419.1 ENSG00000126261.12
## 1 0.09090909 0 0 6035.909
## 2 5.08333333 0 0 5496.083
## 3 0.80000000 0 0 5254.000
## ENSG00000182795.12 ENSG00000006607.13 ENSG00000266065.1
## 1 7676.909 1321.545 0
## 2 1606.750 1895.667 0
## 3 1432.100 1007.300 0
## ENSG00000283047.1 ENSG00000157654.17 ENSG00000252297.1 ENSG00000178082.6
## 1 0.09090909 85.90909 0 8.818182
## 2 134.50000000 47.16667 0 11.750000
## 3 0.30000000 78.70000 0 11.000000
## ENSG00000258994.1 ENSG00000232989.1 ENSG00000168484.12 ENSG00000232144.1
## 1 0 0 1.0909091 0
## 2 0 0 0.4166667 0
## 3 0 0 0.4000000 0
## ENSG00000272333.5 ENSG00000283450.1 ENSG00000270058.1 ENSG00000166225.8
## 1 2239.091 0 0.1818182 778.8182
## 2 3522.917 0 0.0000000 1600.3333
## 3 2699.400 0 0.0000000 1252.1000
## ENSG00000128000.15 ENSG00000240096.1 ENSG00000276493.1 ENSG00000169562.9
## 1 391.5455 0.0000000 0 0.0
## 2 215.1667 0.1666667 0 4.5
## 3 946.5000 0.0000000 0 0.1
## ENSG00000251670.1 ENSG00000253284.2 ENSG00000269678.1 ENSG00000280739.2
## 1 0 2.181818 0 8.727273
## 2 0 3.250000 0 16.833333
## 3 0 5.800000 0 5.500000
## ENSG00000255114.1 ENSG00000211877.1 ENSG00000283164.1 ENSG00000225405.3
## 1 0.09090909 0 0 0
## 2 0.16666667 0 0 0
## 3 0.10000000 0 0 0
## ENSG00000240549.2 ENSG00000224888.4 ENSG00000278413.1 ENSG00000219410.5
## 1 0 1.909091 0 0.00
## 2 0 4.500000 0 0.75
## 3 0 0.700000 0 0.90
## ENSG00000223740.1 ENSG00000106153.12 ENSG00000115970.18
## 1 0 15539.55 1505.818
## 2 0 12946.75 1681.500
## 3 0 7465.60 1828.300
## ENSG00000237001.6 ENSG00000274929.1 ENSG00000260720.1 ENSG00000107438.8
## 1 0 0.9090909 0 14399.636
## 2 0 3.2500000 0 2290.333
## 3 0 2.1000000 0 4285.800
## ENSG00000100916.13 ENSG00000254976.1 ENSG00000111490.12
## 1 632.8182 0 493.2727
## 2 764.5833 0 2135.6667
## 3 900.3000 0 424.0000
## ENSG00000237997.1 ENSG00000143167.11 ENSG00000225122.1 ENSG00000221139.1
## 1 0 0.09090909 0 0
## 2 0 6.91666667 0 0
## 3 0 0.40000000 0 0
## ENSG00000167799.9 ENSG00000253361.1 ENSG00000151929.9 ENSG00000271730.1
## 1 148.0000 0 1591.545 0.0000000
## 2 318.3333 1 3956.833 0.1666667
## 3 85.1000 0 1570.300 0.3000000
## ENSG00000117859.18 ENSG00000207161.1 ENSG00000053438.8 ENSG00000069482.6
## 1 2927.455 0 0.27272727 97.54545
## 2 3205.250 0 0.08333333 795.41667
## 3 5472.400 0 0.00000000 11.90000
## ENSG00000136250.11 ENSG00000254767.1 ENSG00000258593.2
## 1 7.272727 0 7.00
## 2 15.916667 0 8.75
## 3 1.000000 0 11.30
## ENSG00000165966.14 ENSG00000231396.2 ENSG00000130775.15
## 1 3.0000000 0 57.818182
## 2 0.5833333 0 6.166667
## 3 0.4000000 0 20.900000
## ENSG00000153071.14 ENSG00000138074.14 ENSG00000277559.1
## 1 928.27273 2076.636 52.0000
## 2 91.83333 3294.917 118.8333
## 3 855.20000 2772.000 114.1000
## ENSG00000034152.18 ENSG00000007171.16 ENSG00000260909.1
## 1 4526.455 1.727273 0
## 2 2584.583 1.333333 0
## 3 4280.100 1.400000 0
## ENSG00000163518.10 ENSG00000271075.1 ENSG00000279458.2 ENSG00000259342.1
## 1 0.0 0.0 2.818182 0.18181818
## 2 0.0 0.0 0.500000 0.08333333
## 3 0.1 0.3 0.800000 0.10000000
## ENSG00000256385.1 ENSG00000258934.1 ENSG00000271415.1 ENSG00000164199.16
## 1 0.09090909 0 0 4.363636
## 2 0.08333333 0 0 1921.166667
## 3 0.00000000 0 0 352.400000
## ENSG00000183831.6 ENSG00000254718.6 ENSG00000278351.1 ENSG00000089195.14
## 1 1.545455 1.636364 0.00 4210.545
## 2 3.583333 0.250000 0.25 761.000
## 3 1.900000 1.400000 0.00 1965.300
## ENSG00000253910.2 ENSG00000223650.1 ENSG00000223519.8 ENSG00000117335.19
## 1 313.4545 0.18181818 0 10934.636
## 2 20.0000 0.08333333 0 8149.417
## 3 382.1000 0.00000000 0 7958.200
## ENSG00000239280.1 ENSG00000255481.2 ENSG00000266288.1 ENSG00000264755.1
## 1 2.00 0 0 0
## 2 2.25 0 0 0
## 3 3.40 0 0 0
## ENSG00000214807.2 ENSG00000262319.1 ENSG00000251076.1 ENSG00000207769.1
## 1 0.09090909 0.09090909 7.454545 0
## 2 0.25000000 2.16666667 1.500000 0
## 3 0.10000000 1.00000000 1.100000 0
## ENSG00000268940.5 ENSG00000275266.1 ENSG00000244480.1 ENSG00000232511.4
## 1 0.000000 0 7.909091 0.0000000
## 2 3.416667 0 24.583333 0.1666667
## 3 0.000000 0 15.400000 0.0000000
## ENSG00000227835.8 ENSG00000227056.2 ENSG00000213167.3 ENSG00000187118.12
## 1 0.1818182 0 0 329.9091
## 2 0.0000000 0 0 470.0000
## 3 0.2000000 0 0 309.3000
## ENSG00000202395.1 ENSG00000265089.1 ENSG00000227597.1 ENSG00000206604.1
## 1 0 0 0 0
## 2 0 0 0 0
## 3 0 0 0 0
## ENSG00000275638.1 ENSG00000266984.1 ENSG00000271917.1 ENSG00000253932.1
## 1 0.8181818 0 0.09090909 0
## 2 0.6666667 0 0.16666667 0
## 3 1.2000000 0 0.00000000 0
## ENSG00000284690.1 ENSG00000252003.1 ENSG00000254812.1 ENSG00000113558.18
## 1 0.09090909 0 0.4545455 7737.818
## 2 0.25000000 0 3.3333333 10746.917
## 3 0.40000000 0 0.5000000 9339.400
## ENSG00000234197.1 ENSG00000233885.7 ENSG00000109270.12
## 1 0 4.363636 1075.091
## 2 0 4.250000 805.250
## 3 0 6.000000 804.900
## ENSG00000091164.12 ENSG00000244131.2 ENSG00000270147.1 ENSG00000280587.1
## 1 1796.364 0.00000000 3.363636 8.818182
## 2 3913.333 0.08333333 4.333333 28.833333
## 3 3834.300 0.00000000 4.500000 18.200000
## ENSG00000242431.2 ENSG00000224243.1 ENSG00000251066.1 ENSG00000250441.1
## 1 0.00000000 0 1.636364 0.0
## 2 0.08333333 0 4.916667 0.0
## 3 0.00000000 0 3.600000 0.1
## ENSG00000260555.1 ENSG00000207245.1 ENSG00000252041.1 ENSG00000260280.5
## 1 0 0 0 529.4545
## 2 0 0 0 608.3333
## 3 0 0 0 466.4000
## ENSG00000237418.1 ENSG00000171606.17 ENSG00000049167.13
## 1 0.81818182 2695.3636 625.0909
## 2 0.08333333 416.4167 383.8333
## 3 1.30000000 1657.4000 426.7000
## ENSG00000264558.1 ENSG00000254325.2 ENSG00000146250.6 ENSG00000273956.1
## 1 0.0000000 0.09090909 3.818182 0
## 2 0.1666667 0.00000000 40.750000 0
## 3 0.1000000 0.00000000 10.900000 0
## ENSG00000277184.1 ENSG00000229881.1 ENSG00000255320.1 ENSG00000222990.1
## 1 0.00000000 0 0.4545455 0
## 2 0.08333333 0 0.1666667 0
## 3 0.10000000 0 0.4000000 0
## ENSG00000160087.20 ENSG00000259607.1 ENSG00000187170.4 ENSG00000248104.1
## 1 1754.364 0 0 0
## 2 2108.583 0 0 0
## 3 1564.300 0 0 0
## ENSG00000197122.11 ENSG00000267206.5 ENSG00000196313.11
## 1 4273.5455 0.00000000 3165.455
## 2 412.6667 0.08333333 3742.417
## 3 534.1000 0.00000000 3682.700
## ENSG00000232439.1 ENSG00000199710.1 ENSG00000270777.1 ENSG00000099953.9
## 1 0 0 0.1818182 28.18182
## 2 0 0 0.0000000 5.75000
## 3 0 0 0.6000000 21.70000
## ENSG00000201440.1 ENSG00000251313.1 ENSG00000223581.1 ENSG00000239650.4
## 1 0 0.00000000 0 7.454545
## 2 0 0.08333333 0 9.833333
## 3 0 0.00000000 0 19.500000
## ENSG00000143061.17 ENSG00000276929.1 ENSG00000223869.1 ENSG00000258537.5
## 1 1029.818 0 0 0.09090909
## 2 1173.083 0 0 0.08333333
## 3 258.400 0 0 0.00000000
## ENSG00000276070.4 ENSG00000273175.1 ENSG00000240458.1 ENSG00000228136.1
## 1 0.3636364 2.636364 0 0
## 2 0.0000000 1.416667 0 0
## 3 0.0000000 0.400000 0 0
## ENSG00000261325.1 ENSG00000248415.1 ENSG00000232922.1 ENSG00000255700.2
## 1 0.09090909 2.545455 0.0 0
## 2 0.08333333 2.333333 0.5 0
## 3 0.00000000 3.200000 0.1 0
## ENSG00000234828.8 ENSG00000237300.2 ENSG00000083817.8 ENSG00000227409.1
## 1 0.00 0.09090909 393.7273 0
## 2 0.25 0.00000000 165.0833 0
## 3 5.20 0.00000000 230.5000 0
## ENSG00000175985.9 ENSG00000115850.9 ENSG00000234145.1 ENSG00000226080.1
## 1 3.272727 0.4545455 0.9090909 0.1818182
## 2 11.250000 2.0000000 1.9166667 0.0000000
## 3 9.600000 2.5000000 1.5000000 0.0000000
## ENSG00000240419.1 ENSG00000260657.2 ENSG00000264801.1 ENSG00000207087.1
## 1 0 0.4545455 21.000000 0
## 2 0 0.9166667 9.833333 0
## 3 0 0.4000000 11.800000 0
## ENSG00000265799.1 ENSG00000279333.1 ENSG00000211591.1 ENSG00000278598.1
## 1 0.4545455 0.7272727 0 0
## 2 0.0000000 1.1666667 0 0
## 3 0.1000000 2.3000000 0 0
## ENSG00000205643.10 ENSG00000234052.1 ENSG00000243156.7 ENSG00000226876.2
## 1 94.18182 0 1974.182 0
## 2 286.25000 0 2390.333 0
## 3 150.20000 0 2190.000 0
## ENSG00000082175.14 ENSG00000183629.13 ENSG00000145476.15
## 1 0.2727273 27.7272727 583.9091
## 2 0.7500000 0.4166667 496.7500
## 3 0.0000000 15.4000000 1138.3000
table(km$cluster)
##
## 1 2 3
## 11 12 10
plot_heatmap(km)
# Record
sessionInfo()
The sessionInfo() prints version information about R and any attached packages. It’s a good practice to always run this command at the end of your R session and record it for the sake of reproducibility in the future.
sessionInfo()
## R version 3.5.1 (2018-07-02)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 17134)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_United States.1252
## [2] LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] bindrcpp_0.2.2 tidyr_0.8.2 tibble_1.4.2 dplyr_0.7.8
## [5] readr_1.3.0 ggplot2_3.1.0 knitr_1.21
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.0 pillar_1.3.1 compiler_3.5.1 plyr_1.8.4
## [5] bindr_0.1.1 tools_3.5.1 digest_0.6.18 jsonlite_1.6
## [9] evaluate_0.12 gtable_0.2.0 pkgconfig_2.0.2 rlang_0.3.0.1
## [13] yaml_2.2.0 xfun_0.4 withr_2.1.2 stringr_1.3.1
## [17] hms_0.4.2 grid_3.5.1 tidyselect_0.2.5 glue_1.3.0
## [21] R6_2.3.0 rmarkdown_1.11 purrr_0.2.5 magrittr_1.5
## [25] codetools_0.2-15 scales_1.0.0 htmltools_0.3.6 assertthat_0.2.0
## [29] colorspace_1.3-2 labeling_0.3 stringi_1.2.4 lazyeval_0.2.1
## [33] munsell_0.5.0 crayon_1.3.4